class_docstr: Dataset implementation for storing PersonDocuments as records. The augmentation
  and encoding is done using the transform parameter. Returns the encoded documents.
  
  
  :param file:
  :param encoding:
  :param transform:
docstr: Loads the person document from the json data.
docstr_tok: ["Loads","the","person","document","from","the","json","data","."]
code: def deserialize(self, x: str) -> PersonDocument:
      """Loads the person document from the json data."""
      data = json.loads(x)
      data["background"] = Background(**data["background"])
      return PersonDocument(**data)
  
imports: import json
  import logging
  import time
  from dataclasses import asdict
  from pathlib import Path
  from typing import Any, Callable, Generic, Iterable, Optional, TypeVar
  import h5py
  import numpy
  from torch.utils.data import ConcatDataset, Dataset
  from src.tasks.base import Task
  from .types import Background, PersonDocument, EncodedDocument
label_desc: Use image node_id 1 for calling the DocumentDataset obj's underlying member method code with example usage: obj.deserialize(x) and returns: PersonDocument